Tag Archives: Amazon Simple Notification Service (SNS)

Monitoring your Amazon SNS message filtering activity with Amazon CloudWatch

Post Syndicated from Rachel Richardson original https://aws.amazon.com/blogs/compute/monitoring-your-amazon-sns-message-filtering-activity-with-amazon-cloudwatch/

This post is courtesy of Otavio Ferreira, Manager, Amazon SNS, AWS Messaging.

Amazon SNS message filtering provides a set of string and numeric matching operators that allow each subscription to receive only the messages of interest. Hence, SNS message filtering can simplify your pub/sub messaging architecture by offloading the message filtering logic from your subscriber systems, as well as the message routing logic from your publisher systems.

After you set the subscription attribute that defines a filter policy, the subscribing endpoint receives only the messages that carry attributes matching this filter policy. Other messages published to the topic are filtered out for this subscription. In this way, the native integration between SNS and Amazon CloudWatch provides visibility into the number of messages delivered, as well as the number of messages filtered out.

CloudWatch metrics are captured automatically for you. To get started with SNS message filtering, see Filtering Messages with Amazon SNS.

Message Filtering Metrics

The following six CloudWatch metrics are relevant to understanding your SNS message filtering activity:

  • NumberOfMessagesPublished – Inbound traffic to SNS. This metric tracks all the messages that have been published to the topic.
  • NumberOfNotificationsDelivered – Outbound traffic from SNS. This metric tracks all the messages that have been successfully delivered to endpoints subscribed to the topic. A delivery takes place either when the incoming message attributes match a subscription filter policy, or when the subscription has no filter policy at all, which results in a catch-all behavior.
  • NumberOfNotificationsFilteredOut – This metric tracks all the messages that were filtered out because they carried attributes that didn’t match the subscription filter policy.
  • NumberOfNotificationsFilteredOut-NoMessageAttributes – This metric tracks all the messages that were filtered out because they didn’t carry any attributes at all and, consequently, didn’t match the subscription filter policy.
  • NumberOfNotificationsFilteredOut-InvalidAttributes – This metric keeps track of messages that were filtered out because they carried invalid or malformed attributes and, thus, didn’t match the subscription filter policy.
  • NumberOfNotificationsFailed – This last metric tracks all the messages that failed to be delivered to subscribing endpoints, regardless of whether a filter policy had been set for the endpoint. This metric is emitted after the message delivery retry policy is exhausted, and SNS stops attempting to deliver the message. At that moment, the subscribing endpoint is likely no longer reachable. For example, the subscribing SQS queue or Lambda function has been deleted by its owner. You may want to closely monitor this metric to address message delivery issues quickly.

Message filtering graphs

Through the AWS Management Console, you can compose graphs to display your SNS message filtering activity. The graph shows the number of messages published, delivered, and filtered out within the timeframe you specify (1h, 3h, 12h, 1d, 3d, 1w, or custom).

SNS message filtering for CloudWatch Metrics

To compose an SNS message filtering graph with CloudWatch:

  1. Open the CloudWatch console.
  2. Choose Metrics, SNS, All Metrics, and Topic Metrics.
  3. Select all metrics to add to the graph, such as:
    • NumberOfMessagesPublished
    • NumberOfNotificationsDelivered
    • NumberOfNotificationsFilteredOut
  4. Choose Graphed metrics.
  5. In the Statistic column, switch from Average to Sum.
  6. Title your graph with a descriptive name, such as “SNS Message Filtering”

After you have your graph set up, you may want to copy the graph link for bookmarking, emailing, or sharing with co-workers. You may also want to add your graph to a CloudWatch dashboard for easy access in the future. Both actions are available to you on the Actions menu, which is found above the graph.


SNS message filtering defines how SNS topics behave in terms of message delivery. By using CloudWatch metrics, you gain visibility into the number of messages published, delivered, and filtered out. This enables you to validate the operation of filter policies and more easily troubleshoot during development phases.

SNS message filtering can be implemented easily with existing AWS SDKs by applying message and subscription attributes across all SNS supported protocols (Amazon SQS, AWS Lambda, HTTP, SMS, email, and mobile push). CloudWatch metrics for SNS message filtering is available now, in all AWS Regions.

For information about pricing, see the CloudWatch pricing page.

For more information, see:

The End of Google Cloud Messaging, and What it Means for Your Apps

Post Syndicated from Zach Barbitta original https://aws.amazon.com/blogs/messaging-and-targeting/the-end-of-google-cloud-messaging-and-what-it-means-for-your-apps/

On April 10, 2018, Google announced the deprecation of its Google Cloud Messaging (GCM) platform. Specifically, the GCM server and client APIs are deprecated and will be removed as soon as April 11, 2019.  What does this mean for you and your applications that use Amazon Simple Notification Service (Amazon SNS) or Amazon Pinpoint?

First, nothing will break now or after April 11, 2019. GCM device tokens are completely interchangeable with the newer Firebase Cloud Messaging (FCM) device tokens. If you have existing GCM tokens, you’ll still be able to use them to send notifications. This statement is also true for GCM tokens that you generate in the future.

On the back end, we’ve already migrated Amazon SNS and Amazon Pinpoint to the server endpoint for FCM (https://fcm.googleapis.com/fcm/send). As a developer, you don’t need to make any changes as a result of this deprecation.

We created the following mini-FAQ to address some of the questions you may have as a developer who uses Amazon SNS or Amazon Pinpoint.

If I migrate to FCM from GCM, can I still use Amazon Pinpoint and Amazon SNS?

Yes. Your ability to connect to your applications and send messages through both Amazon SNS and Amazon Pinpoint doesn’t change. We’ll update the documentation for Amazon SNS and Amazon Pinpoint soon to reflect these changes.

If I don’t migrate to FCM from GCM, can I still use Amazon Pinpoint and Amazon SNS?

Yes. If you do nothing, your existing credentials and GCM tokens will still be valid. All applications that you previously set up to use Amazon Pinpoint or Amazon SNS will continue to work normally. When you call the API for Amazon Pinpoint or Amazon SNS, we initiate a request to the FCM server endpoint directly.

What are the differences between Amazon SNS and Amazon Pinpoint?

Amazon SNS makes it easy for developers to set up, operate, and send notifications at scale, affordably and with a high degree of flexibility. Amazon Pinpoint has many of the same messaging capabilities as Amazon SNS, with the same levels of scalability and flexibility.

The main difference between the two services is that Amazon Pinpoint provides both transactional and targeted messaging capabilities. By using Amazon Pinpoint, marketers and developers can not only send transactional messages to their customers, but can also segment their audiences, create campaigns, and analyze both application and message metrics.

How do I migrate from GCM to FCM?

For more information about migrating from GCM to FCM, see Migrate a GCM Client App for Android to Firebase Cloud Messaging on the Google Developers site.

If you have any questions, please post them in the comments section, or in the Amazon Pinpoint or Amazon SNS forums.

Securing messages published to Amazon SNS with AWS PrivateLink

Post Syndicated from Otavio Ferreira original https://aws.amazon.com/blogs/security/securing-messages-published-to-amazon-sns-with-aws-privatelink/

Amazon Simple Notification Service (SNS) now supports VPC Endpoints (VPCE) via AWS PrivateLink. You can use VPC Endpoints to privately publish messages to SNS topics, from an Amazon Virtual Private Cloud (VPC), without traversing the public internet. When you use AWS PrivateLink, you don’t need to set up an Internet Gateway (IGW), Network Address Translation (NAT) device, or Virtual Private Network (VPN) connection. You don’t need to use public IP addresses, either.

VPC Endpoints doesn’t require code changes and can bring additional security to Pub/Sub Messaging use cases that rely on SNS. VPC Endpoints helps promote data privacy and is aligned with assurance programs, including the Health Insurance Portability and Accountability Act (HIPAA), FedRAMP, and others discussed below.

VPC Endpoints for SNS in action

Here’s how VPC Endpoints for SNS works. The following example is based on a banking system that processes mortgage applications. This banking system, which has been deployed to a VPC, publishes each mortgage application to an SNS topic. The SNS topic then fans out the mortgage application message to two subscribing AWS Lambda functions:

  • Save-Mortgage-Application stores the application in an Amazon DynamoDB table. As the mortgage application contains personally identifiable information (PII), the message must not traverse the public internet.
  • Save-Credit-Report checks the applicant’s credit history against an external Credit Reporting Agency (CRA), then stores the final credit report in an Amazon S3 bucket.

The following diagram depicts the underlying architecture for this banking system:
Diagram depicting the architecture for the example banking system
To protect applicants’ data, the financial institution responsible for developing this banking system needed a mechanism to prevent PII data from traversing the internet when publishing mortgage applications from their VPC to the SNS topic. Therefore, they created a VPC endpoint to enable their publisher Amazon EC2 instance to privately connect to the SNS API. As shown in the diagram, when the VPC endpoint is created, an Elastic Network Interface (ENI) is automatically placed in the same VPC subnet as the publisher EC2 instance. This ENI exposes a private IP address that is used as the entry point for traffic destined to SNS. This ensures that traffic between the VPC and SNS doesn’t leave the Amazon network.

Set up VPC Endpoints for SNS

The process for creating a VPC endpoint to privately connect to SNS doesn’t require code changes: access the VPC Management Console, navigate to the Endpoints section, and create a new Endpoint. Three attributes are required:

  • The SNS service name.
  • The VPC and Availability Zones (AZs) from which you’ll publish your messages.
  • The Security Group (SG) to be associated with the endpoint network interface. The Security Group controls the traffic to the endpoint network interface from resources in your VPC. If you don’t specify a Security Group, the default Security Group for your VPC will be associated.

Help ensure your security and compliance

SNS can support messaging use cases in regulated market segments, such as healthcare provider systems subject to the Health Insurance Portability and Accountability Act (HIPAA) and financial systems subject to the Payment Card Industry Data Security Standard (PCI DSS), and is also in-scope with the following Assurance Programs:

The SNS API is served through HTTP Secure (HTTPS), and encrypts all messages in transit with Transport Layer Security (TLS) certificates issued by Amazon Trust Services (ATS). The certificates verify the identity of the SNS API server when encrypted connections are established. The certificates help establish proof that your SNS API client (SDK, CLI) is communicating securely with the SNS API server. A Certificate Authority (CA) issues the certificate to a specific domain. Hence, when a domain presents a certificate that’s issued by a trusted CA, the SNS API client knows it’s safe to make the connection.


VPC Endpoints can increase the security of your pub/sub messaging use cases by allowing you to publish messages to SNS topics, from instances in your VPC, without traversing the internet. Setting up VPC Endpoints for SNS doesn’t require any code changes because the SNS API address remains the same.

VPC Endpoints for SNS is now available in all AWS Regions where AWS PrivateLink is available. For information on pricing and regional availability, visit the VPC pricing page.
For more information and on-boarding, see Publishing to Amazon SNS Topics from Amazon Virtual Private Cloud in the SNS documentation.

If you have comments about this post, submit them in the Comments section below. If you have questions about anything in this post, start a new thread on the Amazon SNS forum or contact AWS Support.

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Message Filtering Operators for Numeric Matching, Prefix Matching, and Blacklisting in Amazon SNS

Post Syndicated from Christie Gifrin original https://aws.amazon.com/blogs/compute/message-filtering-operators-for-numeric-matching-prefix-matching-and-blacklisting-in-amazon-sns/

This blog was contributed by Otavio Ferreira, Software Development Manager for Amazon SNS

Message filtering simplifies the overall pub/sub messaging architecture by offloading message filtering logic from subscribers, as well as message routing logic from publishers. The initial launch of message filtering provided a basic operator that was based on exact string comparison. For more information, see Simplify Your Pub/Sub Messaging with Amazon SNS Message Filtering.

Today, AWS is announcing an additional set of filtering operators that bring even more power and flexibility to your pub/sub messaging use cases.

Message filtering operators

Amazon SNS now supports both numeric and string matching. Specifically, string matching operators allow for exact, prefix, and “anything-but” comparisons, while numeric matching operators allow for exact and range comparisons, as outlined below. Numeric matching operators work for values between -10e9 and +10e9 inclusive, with five digits of accuracy right of the decimal point.

  • Exact matching on string values (Whitelisting): Subscription filter policy   {"sport": ["rugby"]} matches message attribute {"sport": "rugby"} only.
  • Anything-but matching on string values (Blacklisting): Subscription filter policy {"sport": [{"anything-but": "rugby"}]} matches message attributes such as {"sport": "baseball"} and {"sport": "basketball"} and {"sport": "football"} but not {"sport": "rugby"}
  • Prefix matching on string values: Subscription filter policy {"sport": [{"prefix": "bas"}]} matches message attributes such as {"sport": "baseball"} and {"sport": "basketball"}
  • Exact matching on numeric values: Subscription filter policy {"balance": [{"numeric": ["=", 301.5]}]} matches message attributes {"balance": 301.500} and {"balance": 3.015e2}
  • Range matching on numeric values: Subscription filter policy {"balance": [{"numeric": ["<", 0]}]} matches negative numbers only, and {"balance": [{"numeric": [">", 0, "<=", 150]}]} matches any positive number up to 150.

As usual, you may apply the “AND” logic by appending multiple keys in the subscription filter policy, and the “OR” logic by appending multiple values for the same key, as follows:

  • AND logic: Subscription filter policy {"sport": ["rugby"], "language": ["English"]} matches only messages that carry both attributes {"sport": "rugby"} and {"language": "English"}
  • OR logic: Subscription filter policy {"sport": ["rugby", "football"]} matches messages that carry either the attribute {"sport": "rugby"} or {"sport": "football"}

Message filtering operators in action

Here’s how this new set of filtering operators works. The following example is based on a pharmaceutical company that develops, produces, and markets a variety of prescription drugs, with research labs located in Asia Pacific and Europe. The company built an internal procurement system to manage the purchasing of lab supplies (for example, chemicals and utensils), office supplies (for example, paper, folders, and markers) and tech supplies (for example, laptops, monitors, and printers) from global suppliers.

This distributed system is composed of the four following subsystems:

  • A requisition system that presents the catalog of products from suppliers, and takes orders from buyers
  • An approval system for orders targeted to Asia Pacific labs
  • Another approval system for orders targeted to European labs
  • A fulfillment system that integrates with shipping partners

As shown in the following diagram, the company leverages AWS messaging services to integrate these distributed systems.

  • Firstly, an SNS topic named “Orders” was created to take all orders placed by buyers on the requisition system.
  • Secondly, two Amazon SQS queues, named “Lab-Orders-AP” and “Lab-Orders-EU” (for Asia Pacific and Europe respectively), were created to backlog orders that are up for review on the approval systems.
  • Lastly, an SQS queue named “Common-Orders” was created to backlog orders that aren’t related to lab supplies, which can already be picked up by shipping partners on the fulfillment system.

The company also uses AWS Lambda functions to automatically process lab supply orders that don’t require approval or which are invalid.

In this example, because different types of orders have been published to the SNS topic, the subscribing endpoints have had to set advanced filter policies on their SNS subscriptions, to have SNS automatically filter out orders they can’t deal with.

As depicted in the above diagram, the following five filter policies have been created:

  • The SNS subscription that points to the SQS queue “Lab-Orders-AP” sets a filter policy that matches lab supply orders, with a total value greater than $1,000, and that target Asia Pacific labs only. These more expensive transactions require an approver to review orders placed by buyers.
  • The SNS subscription that points to the SQS queue “Lab-Orders-EU” sets a filter policy that matches lab supply orders, also with a total value greater than $1,000, but that target European labs instead.
  • The SNS subscription that points to the Lambda function “Lab-Preapproved” sets a filter policy that only matches lab supply orders that aren’t as expensive, up to $1,000, regardless of their target lab location. These orders simply don’t require approval and can be automatically processed.
  • The SNS subscription that points to the Lambda function “Lab-Cancelled” sets a filter policy that only matches lab supply orders with total value of $0 (zero), regardless of their target lab location. These orders carry no actual items, obviously need neither approval nor fulfillment, and as such can be automatically canceled.
  • The SNS subscription that points to the SQS queue “Common-Orders” sets a filter policy that blacklists lab supply orders. Hence, this policy matches only office and tech supply orders, which have a more streamlined fulfillment process, and require no approval, regardless of price or target location.

After the company finished building this advanced pub/sub architecture, they were then able to launch their internal procurement system and allow buyers to begin placing orders. The diagram above shows six example orders published to the SNS topic. Each order contains message attributes that describe the order, and cause them to be filtered in a different manner, as follows:

  • Message #1 is a lab supply order, with a total value of $15,700 and targeting a research lab in Singapore. Because the value is greater than $1,000, and the location “Asia-Pacific-Southeast” matches the prefix “Asia-Pacific-“, this message matches the first SNS subscription and is delivered to SQS queue “Lab-Orders-AP”.
  • Message #2 is a lab supply order, with a total value of $1,833 and targeting a research lab in Ireland. Because the value is greater than $1,000, and the location “Europe-West” matches the prefix “Europe-“, this message matches the second SNS subscription and is delivered to SQS queue “Lab-Orders-EU”.
  • Message #3 is a lab supply order, with a total value of $415. Because the value is greater than $0 and less than $1,000, this message matches the third SNS subscription and is delivered to Lambda function “Lab-Preapproved”.
  • Message #4 is a lab supply order, but with a total value of $0. Therefore, it only matches the fourth SNS subscription, and is delivered to Lambda function “Lab-Cancelled”.
  • Messages #5 and #6 aren’t lab supply orders actually; one is an office supply order, and the other is a tech supply order. Therefore, they only match the fifth SNS subscription, and are both delivered to SQS queue “Common-Orders”.

Although each message only matched a single subscription, each was tested against the filter policy of every subscription in the topic. Hence, depending on which attributes are set on the incoming message, the message might actually match multiple subscriptions, and multiple deliveries will take place. Also, it is important to bear in mind that subscriptions with no filter policies catch every single message published to the topic, as a blank filter policy equates to a catch-all behavior.


Amazon SNS allows for both string and numeric filtering operators. As explained in this post, string operators allow for exact, prefix, and “anything-but” comparisons, while numeric operators allow for exact and range comparisons. These advanced filtering operators bring even more power and flexibility to your pub/sub messaging functionality and also allow you to simplify your architecture further by removing even more logic from your subscribers.

Message filtering can be implemented easily with existing AWS SDKs by applying message and subscription attributes across all SNS supported protocols (Amazon SQS, AWS Lambda, HTTP, SMS, email, and mobile push). SNS filtering operators for numeric matching, prefix matching, and blacklisting are available now in all AWS Regions, for no extra charge.

To experiment with these new filtering operators yourself, and continue learning, try the 10-minute Tutorial Filter Messages Published to Topics. For more information, see Filtering Messages with Amazon SNS in the SNS documentation.

Now Open AWS EU (Paris) Region

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/now-open-aws-eu-paris-region/

Today we are launching our 18th AWS Region, our fourth in Europe. Located in the Paris area, AWS customers can use this Region to better serve customers in and around France.

The Details
The new EU (Paris) Region provides a broad suite of AWS services including Amazon API Gateway, Amazon Aurora, Amazon CloudFront, Amazon CloudWatch, CloudWatch Events, Amazon CloudWatch Logs, Amazon DynamoDB, Amazon Elastic Compute Cloud (EC2), EC2 Container Registry, Amazon ECS, Amazon Elastic Block Store (EBS), Amazon EMR, Amazon ElastiCache, Amazon Elasticsearch Service, Amazon Glacier, Amazon Kinesis Streams, Polly, Amazon Redshift, Amazon Relational Database Service (RDS), Amazon Route 53, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), Amazon Simple Storage Service (S3), Amazon Simple Workflow Service (SWF), Amazon Virtual Private Cloud, Auto Scaling, AWS Certificate Manager (ACM), AWS CloudFormation, AWS CloudTrail, AWS CodeDeploy, AWS Config, AWS Database Migration Service, AWS Direct Connect, AWS Elastic Beanstalk, AWS Identity and Access Management (IAM), AWS Key Management Service (KMS), AWS Lambda, AWS Marketplace, AWS OpsWorks Stacks, AWS Personal Health Dashboard, AWS Server Migration Service, AWS Service Catalog, AWS Shield Standard, AWS Snowball, AWS Snowball Edge, AWS Snowmobile, AWS Storage Gateway, AWS Support (including AWS Trusted Advisor), Elastic Load Balancing, and VM Import.

The Paris Region supports all sizes of C5, M5, R4, T2, D2, I3, and X1 instances.

There are also four edge locations for Amazon Route 53 and Amazon CloudFront: three in Paris and one in Marseille, all with AWS WAF and AWS Shield. Check out the AWS Global Infrastructure page to learn more about current and future AWS Regions.

The Paris Region will benefit from three AWS Direct Connect locations. Telehouse Voltaire is available today. AWS Direct Connect will also become available at Equinix Paris in early 2018, followed by Interxion Paris.

All AWS infrastructure regions around the world are designed, built, and regularly audited to meet the most rigorous compliance standards and to provide high levels of security for all AWS customers. These include ISO 27001, ISO 27017, ISO 27018, SOC 1 (Formerly SAS 70), SOC 2 and SOC 3 Security & Availability, PCI DSS Level 1, and many more. This means customers benefit from all the best practices of AWS policies, architecture, and operational processes built to satisfy the needs of even the most security sensitive customers.

AWS is certified under the EU-US Privacy Shield, and the AWS Data Processing Addendum (DPA) is GDPR-ready and available now to all AWS customers to help them prepare for May 25, 2018 when the GDPR becomes enforceable. The current AWS DPA, as well as the AWS GDPR DPA, allows customers to transfer personal data to countries outside the European Economic Area (EEA) in compliance with European Union (EU) data protection laws. AWS also adheres to the Cloud Infrastructure Service Providers in Europe (CISPE) Code of Conduct. The CISPE Code of Conduct helps customers ensure that AWS is using appropriate data protection standards to protect their data, consistent with the GDPR. In addition, AWS offers a wide range of services and features to help customers meet the requirements of the GDPR, including services for access controls, monitoring, logging, and encryption.

From Our Customers
Many AWS customers are preparing to use this new Region. Here’s a small sample:

Societe Generale, one of the largest banks in France and the world, has accelerated their digital transformation while working with AWS. They developed SG Research, an application that makes reports from Societe Generale’s analysts available to corporate customers in order to improve the decision-making process for investments. The new AWS Region will reduce latency between applications running in the cloud and in their French data centers.

SNCF is the national railway company of France. Their mobile app, powered by AWS, delivers real-time traffic information to 14 million riders. Extreme weather, traffic events, holidays, and engineering works can cause usage to peak at hundreds of thousands of users per second. They are planning to use machine learning and big data to add predictive features to the app.

Radio France, the French public radio broadcaster, offers seven national networks, and uses AWS to accelerate its innovation and stay competitive.

Les Restos du Coeur, a French charity that provides assistance to the needy, delivering food packages and participating in their social and economic integration back into French society. Les Restos du Coeur is using AWS for its CRM system to track the assistance given to each of their beneficiaries and the impact this is having on their lives.

AlloResto by JustEat (a leader in the French FoodTech industry), is using AWS to to scale during traffic peaks and to accelerate their innovation process.

AWS Consulting and Technology Partners
We are already working with a wide variety of consulting, technology, managed service, and Direct Connect partners in France. Here’s a partial list:

AWS Premier Consulting PartnersAccenture, Capgemini, Claranet, CloudReach, DXC, and Edifixio.

AWS Consulting PartnersABC Systemes, Atos International SAS, CoreExpert, Cycloid, Devoteam, LINKBYNET, Oxalide, Ozones, Scaleo Information Systems, and Sopra Steria.

AWS Technology PartnersAxway, Commerce Guys, MicroStrategy, Sage, Software AG, Splunk, Tibco, and Zerolight.

AWS in France
We have been investing in Europe, with a focus on France, for the last 11 years. We have also been developing documentation and training programs to help our customers to improve their skills and to accelerate their journey to the AWS Cloud.

As part of our commitment to AWS customers in France, we plan to train more than 25,000 people in the coming years, helping them develop highly sought after cloud skills. They will have access to AWS training resources in France via AWS Academy, AWSome days, AWS Educate, and webinars, all delivered in French by AWS Technical Trainers and AWS Certified Trainers.

Use it Today
The EU (Paris) Region is open for business now and you can start using it today!



Now Open – AWS China (Ningxia) Region

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/now-open-aws-china-ningxia-region/

Today we launched our 17th Region globally, and the second in China. The AWS China (Ningxia) Region, operated by Ningxia Western Cloud Data Technology Co. Ltd. (NWCD), is generally available now and provides customers another option to run applications and store data on AWS in China.

The Details
At launch, the new China (Ningxia) Region, operated by NWCD, supports Auto Scaling, AWS Config, AWS CloudFormation, AWS CloudTrail, Amazon CloudWatch, CloudWatch Events, Amazon CloudWatch Logs, AWS CodeDeploy, AWS Direct Connect, Amazon DynamoDB, Amazon Elastic Compute Cloud (EC2), Amazon Elastic Block Store (EBS), Amazon EC2 Systems Manager, AWS Elastic Beanstalk, Amazon ElastiCache, Amazon Elasticsearch Service, Elastic Load Balancing, Amazon EMR, Amazon Glacier, AWS Identity and Access Management (IAM), Amazon Kinesis Streams, Amazon Redshift, Amazon Relational Database Service (RDS), Amazon Simple Storage Service (S3), Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), AWS Support API, AWS Trusted Advisor, Amazon Simple Workflow Service (SWF), Amazon Virtual Private Cloud, and VM Import. Visit the AWS China Products page for additional information on these services.

The Region supports all sizes of C4, D2, M4, T2, R4, I3, and X1 instances.

Check out the AWS Global Infrastructure page to learn more about current and future AWS Regions.

Operating Partner
To comply with China’s legal and regulatory requirements, AWS has formed a strategic technology collaboration with NWCD to operate and provide services from the AWS China (Ningxia) Region. Founded in 2015, NWCD is a licensed datacenter and cloud services provider, based in Ningxia, China. NWCD joins Sinnet, the operator of the AWS China China (Beijing) Region, as an AWS operating partner in China. Through these relationships, AWS provides its industry-leading technology, guidance, and expertise to NWCD and Sinnet, while NWCD and Sinnet operate and provide AWS cloud services to local customers. While the cloud services offered in both AWS China Regions are the same as those available in other AWS Regions, the AWS China Regions are different in that they are isolated from all other AWS Regions and operated by AWS’s Chinese partners separately from all other AWS Regions. Customers using the AWS China Regions enter into customer agreements with Sinnet and NWCD, rather than with AWS.

Use it Today
The AWS China (Ningxia) Region, operated by NWCD, is open for business, and you can start using it now! Starting today, Chinese developers, startups, and enterprises, as well as government, education, and non-profit organizations, can leverage AWS to run their applications and store their data in the new AWS China (Ningxia) Region, operated by NWCD. Customers already using the AWS China (Beijing) Region, operated by Sinnet, can select the AWS China (Ningxia) Region directly from the AWS Management Console, while new customers can request an account at www.amazonaws.cn to begin using both AWS China Regions.




Amazon MQ – Managed Message Broker Service for ActiveMQ

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/amazon-mq-managed-message-broker-service-for-activemq/

Messaging holds the parts of a distributed application together, while also adding resiliency and enabling the implementation of highly scalable architectures. For example, earlier this year, Amazon Simple Queue Service (SQS) and Amazon Simple Notification Service (SNS) supported the processing of customer orders on Prime Day, collectively processing 40 billion messages at a rate of 10 million per second, with no customer-visible issues.

SQS and SNS have been used extensively for applications that were born in the cloud. However, many of our larger customers are already making use of open-sourced or commercially-licensed message brokers. Their applications are mission-critical, and so is the messaging that powers them. Our customers describe the setup and on-going maintenance of their messaging infrastructure as “painful” and report that they spend at least 10 staff-hours per week on this chore.

New Amazon MQ
Today we are launching Amazon MQ – a managed message broker service for Apache ActiveMQ that lets you get started in minutes with just three clicks! As you may know, ActiveMQ is a popular open-source message broker that is fast & feature-rich. It offers queues and topics, durable and non-durable subscriptions, push-based and poll-based messaging, and filtering.

As a managed service, Amazon MQ takes care of the administration and maintenance of ActiveMQ. This includes responsibility for broker provisioning, patching, failure detection & recovery for high availability, and message durability. With Amazon MQ, you get direct access to the ActiveMQ console and industry standard APIs and protocols for messaging, including JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. This allows you to move from any message broker that uses these standards to Amazon MQ–along with the supported applications–without rewriting code.

You can create a single-instance Amazon MQ broker for development and testing, or an active/standby pair that spans AZs, with quick, automatic failover. Either way, you get data replication across AZs and a pay-as-you-go model for the broker instance and message storage.

Amazon MQ is a full-fledged part of the AWS family, including the use of AWS Identity and Access Management (IAM) for authentication and authorization to use the service API. You can use Amazon CloudWatch metrics to keep a watchful eye metrics such as queue depth and initiate Auto Scaling of your consumer fleet as needed.

Launching an Amazon MQ Broker
To get started, I open up the Amazon MQ Console, select the desired AWS Region, enter a name for my broker, and click on Next step:

Then I choose the instance type, indicate that I want to create a standby , and click on Create broker (I can select a VPC and fine-tune other settings in the Advanced settings section):

My broker will be created and ready to use in 5-10 minutes:

The URLs and endpoints that I use to access my broker are all available at a click:

I can access the ActiveMQ Web Console at the link provided:

The broker publishes instance, topic, and queue metrics to CloudWatch. Here are the instance metrics:

Available Now
Amazon MQ is available now and you can start using it today in the US East (Northern Virginia), US East (Ohio), US West (Oregon), EU (Ireland), EU (Frankfurt), and Asia Pacific (Sydney) Regions.

The AWS Free Tier lets you use a single-AZ micro instance for up to 750 hours and to store up to 1 gigabyte each month, for one year. After that, billing is based on instance-hours and message storage, plus charges Internet data transfer if the broker is accessed from outside of AWS.


Serverless Automated Cost Controls, Part1

Post Syndicated from Shankar Ramachandran original https://aws.amazon.com/blogs/compute/serverless-automated-cost-controls-part1/

This post courtesy of Shankar Ramachandran, Pubali Sen, and George Mao

In line with AWS’s continual efforts to reduce costs for customers, this series focuses on how customers can build serverless automated cost controls. This post provides an architecture blueprint and a sample implementation to prevent budget overruns.

This solution uses the following AWS products:

  • AWS Budgets – An AWS Cost Management tool that helps customers define and track budgets for AWS costs, and forecast for up to three months.
  • Amazon SNS – An AWS service that makes it easy to set up, operate, and send notifications from the cloud.
  • AWS Lambda – An AWS service that lets you run code without provisioning or managing servers.

You can fine-tune a budget for various parameters, for example filtering by service or tag. The Budgets tool lets you post notifications on an SNS topic. A Lambda function that subscribes to the SNS topic can act on the notification. Any programmatically implementable action can be taken.

The diagram below describes the architecture blueprint.

In this post, we describe how to use this blueprint with AWS Step Functions and IAM to effectively revoke the ability of a user to start new Amazon EC2 instances, after a budget amount is exceeded.

Freedom with guardrails

AWS lets you quickly spin up resources as you need them, deploying hundreds or even thousands of servers in minutes. This means you can quickly develop and roll out new applications. Teams can experiment and innovate more quickly and frequently. If an experiment fails, you can always de-provision those servers without risk.

This improved agility also brings in the need for effective cost controls. Your Finance and Accounting department must budget, monitor, and control the AWS spend. For example, this could be a budget per project. Further, Finance and Accounting must take appropriate actions if the budget for the project has been exceeded, for example. Call it “freedom with guardrails” – where Finance wants to give developers freedom, but with financial constraints.


This section describes how to use the blueprint introduced earlier to implement a “freedom with guardrails” solution.

  1. The budget for “Project Beta” is set up in Budgets. In this example, we focus on EC2 usage and identify the instances that belong to this project by filtering on the tag Project with the value Beta. For more information, see Creating a Budget.
  2. The budget configuration also includes settings to send a notification on an SNS topic when the usage exceeds 100% of the budgeted amount. For more information, see Creating an Amazon SNS Topic for Budget Notifications.
  3. The master Lambda function receives the SNS notification.
  4. It triggers execution of a Step Functions state machine with the parameters for completing the configured action.
  5. The action Lambda function is triggered as a task in the state machine. The function interacts with IAM to effectively remove the user’s permissions to create an EC2 instance.

This decoupled modular design allows for extensibility.  New actions (serially or in parallel) can be added by simply adding new steps.

Implementing the solution

All the instructions and code needed to implement the architecture have been posted on the Serverless Automated Cost Controls GitHub repo. We recommend that you try this first in a Dev/Test environment.

This implementation description can be broken down into two parts:

  1. Create a solution stack for serverless automated cost controls.
  2. Verify the solution by testing the EC2 fleet.

To tie this back to the “freedom with guardrails” scenario, the Finance department performs a one-time implementation of the solution stack. To simulate resources for Project Beta, the developers spin up the test EC2 fleet.


There are two prerequisites:

  • Make sure that you have the necessary IAM permissions. For more information, see the section titled “Required IAM permissions” in the README.
  • Define and activate a cost allocation tag with the key Project. For more information, see Using Cost Allocation Tags. It can take up to 12 hours for the tags to propagate to Budgets.

Create resources

The solution stack includes creating the following resources:

  • Three Lambda functions
  • One Step Functions state machine
  • One SNS topic
  • One IAM group
  • One IAM user
  • IAM policies as needed
  • One budget

Two of the Lambda functions were described in the previous section, to a) receive the SNS notification and b) trigger the Step Functions state machine. Another Lambda function is used to create the budget, as a custom AWS CloudFormation resource. The SNS topic connects Budgets with Lambda function A. Lambda function B is configured as a task in Step Functions. A budget for $2 is created which is filtered by Service: EC2 and Tag: Project, Beta. A test IAM group and user is created to enable you to validate this Cost Control Solution.

To create the serverless automated cost control solution stack, choose the button below. It takes few minutes to spin up the stack. You can monitor the progress in the CloudFormation console.

When you see the CREATE_COMPLETE status for the stack you had created, choose Outputs. Copy the following four values that you need later:

  • TemplateURL
  • UserName
  • SignInURL
  • Password

Verify the stack

The next step is to verify the serverless automated cost controls solution stack that you just created. To do this, spin up an EC2 fleet of t2.micro instances, representative of the resources needed for Project Beta, and tag them with Project, Beta.

  1. Browse to the SignInURL, and log in using the UserName and Password values copied on from the stack output.
  2. In the CloudFormation console, choose Create Stack.
  3. For Choose a template, select Choose an Amazon S3 template URL and paste the TemplateURL value from the preceding section. Choose Next.
  4. Give this stack a name, such as “testEc2FleetForProjectBeta”. Choose Next.
  5. On the Specify Details page, enter parameters such as the UserName and Password copied in the previous section. Choose Next.
  6. Ignore any errors related to listing IAM roles. The test user has a minimal set of permissions that is just sufficient to spin up this test stack (in line with security best practices).
  7. On the Options page, choose Next.
  8. On the Review page, choose Create. It takes a few minutes to spin up the stack, and you can monitor the progress in the CloudFormation console. 
  9. When you see the status “CREATE_COMPLETE”, open the EC2 console to verify that four t2.micro instances have been spun up, with the tag of Project, Beta.

The hourly cost for these instances depends on the region in which they are running. On the average (irrespective of the region), you can expect the aggregate cost for this EC2 fleet to exceed the set $2 budget in 48 hours.

Verify the solution

The first step is to identify the test IAM group that was created in the previous section. The group should have “projectBeta” in the name, prepended with the CloudFormation stack name and appended with an alphanumeric string. Verify that the managed policy associated is: “EC2FullAccess”, which indicates that the users in this group have unrestricted access to EC2.

There are two stages of verification for this serverless automated cost controls solution: simulating a notification and waiting for a breach.

Simulated notification

Because it takes at least a few hours for the aggregate cost of the EC2 fleet to breach the set budget, you can verify the solution by simulating the notification from Budgets.

  1. Log in to the SNS console (using your regular AWS credentials).
  2. Publish a message on the SNS topic that has “budgetNotificationTopic” in the name. The complete name is appended by the CloudFormation stack identifier.  
  3. Copy the following text as the body of the notification: “This is a mock notification”.
  4. Choose Publish.
  5. Open the IAM console to verify that the policy for the test group has been switched to “EC2ReadOnly”. This prevents users in this group from creating new instances.
  6. Verify that the test user created in the previous section cannot spin up new EC2 instances.  You can log in as the test user and try creating a new EC2 instance (via the same CloudFormation stack or the EC2 console). You should get an error message indicating that you do not have the necessary permissions.
  7. If you are proceeding to stage 2 of the verification, then you must switch the permissions back to “EC2FullAccess” for the test group, which can be done in the IAM console.

Automatic notification

Within 48 hours, the aggregate cost of the EC2 fleet spun up in the earlier section breaches the budget rule and triggers an automatic notification. This results in the permissions getting switched out, just as in the simulated notification.

Clean up

Use the following steps to delete your resources and stop incurring costs.

  1. Open the CloudFormation console.
  2. Delete the EC2 fleet by deleting the appropriate stack (for example, delete the stack named “testEc2FleetForProjectBeta”).                                               
  3. Next, delete the “costControlStack” stack.                                                                                                                                                    


Using Lambda in tandem with Budgets, you can build Serverless automated cost controls on AWS. Find all the resources (instructions, code) for implementing the solution discussed in this post on the Serverless Automated Cost Controls GitHub repo.

Stay tuned to this series for more tips about building serverless automated cost controls. In the next post, we discuss using smart lighting to influence developer behavior and describe a solution to encourage cost-aware development practices.

If you have questions or suggestions, please comment below.


AWS IoT Update – Better Value with New Pricing Model

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/aws-iot-update-better-value-with-new-pricing-model/

Our customers are using AWS IoT to make their connected devices more intelligent. These devices collect & measure data in the field (below the ground, in the air, in the water, on factory floors and in hospital rooms) and use AWS IoT as their gateway to the AWS Cloud. Once connected to the cloud, customers can write device data to Amazon Simple Storage Service (S3) and Amazon DynamoDB, process data using Amazon Kinesis and AWS Lambda functions, initiate Amazon Simple Notification Service (SNS) push notifications, and much more.

New Pricing Model (20-40% Reduction)
Today we are making a change to the AWS IoT pricing model that will make it an even better value for you. Most customers will see a price reduction of 20-40%, with some receiving a significantly larger discount depending on their workload.

The original model was based on a charge for the number of messages that were sent to or from the service. This all-inclusive model was a good starting point, but also meant that some customers were effectively paying for parts of AWS IoT that they did not actually use. For example, some customers have devices that ping AWS IoT very frequently, with sparse rule sets that fire infrequently. Our new model is more fine-grained, with independent charges for each component (all prices are for devices that connect to the US East (Northern Virginia) Region):

Connectivity – Metered in 1 minute increments and based on the total time your devices are connected to AWS IoT. Priced at $0.08 per million minutes of connection (equivalent to $0.042 per device per year for 24/7 connectivity). Your devices can send keep-alive pings at 30 second to 20 minute intervals at no additional cost.

Messaging – Metered by the number of messages transmitted between your devices and AWS IoT. Pricing starts at $1 per million messages, with volume pricing falling as low as $0.70 per million. You may send and receive messages up to 128 kilobytes in size. Messages are metered in 5 kilobyte increments (up from 512 bytes previously). For example, an 8 kilobyte message is metered as two messages.

Rules Engine – Metered for each time a rule is triggered, and for the number of actions executed within a rule, with a minimum of one action per rule. Priced at $0.15 per million rules-triggered and $0.15 per million actions-executed. Rules that process a message in excess of 5 kilobytes are metered at the next multiple of the 5 kilobyte size. For example, a rule that processes an 8 kilobyte message is metered as two rules.

Device Shadow & Registry Updates – Metered on the number of operations to access or modify Device Shadow or Registry data, priced at $1.25 per million operations. Device Shadow and Registry operations are metered in 1 kilobyte increments of the Device Shadow or Registry record size. For example, an update to a 1.5 kilobyte Shadow record is metered as two operations.

The AWS Free Tier now offers a generous allocation of connection minutes, messages, triggered rules, rules actions, Shadow, and Registry usage, enough to operate a fleet of up to 50 devices. The new prices will take effect on January 1, 2018 with no effort on your part. At that time, the updated prices will be published on the AWS IoT Pricing page.

AWS IoT at re:Invent
We have an entire IoT track at this year’s AWS re:Invent. Here is a sampling:

We also have customer-led sessions from Philips, Panasonic, Enel, and Salesforce.


Event-Driven Computing with Amazon SNS and AWS Compute, Storage, Database, and Networking Services

Post Syndicated from Christie Gifrin original https://aws.amazon.com/blogs/compute/event-driven-computing-with-amazon-sns-compute-storage-database-and-networking-services/

Contributed by Otavio Ferreira, Manager, Software Development, AWS Messaging

Like other developers around the world, you may be tackling increasingly complex business problems. A key success factor, in that case, is the ability to break down a large project scope into smaller, more manageable components. A service-oriented architecture guides you toward designing systems as a collection of loosely coupled, independently scaled, and highly reusable services. Microservices take this even further. To improve performance and scalability, they promote fine-grained interfaces and lightweight protocols.

However, the communication among isolated microservices can be challenging. Services are often deployed onto independent servers and don’t share any compute or storage resources. Also, you should avoid hard dependencies among microservices, to preserve maintainability and reusability.

If you apply the pub/sub design pattern, you can effortlessly decouple and independently scale out your microservices and serverless architectures. A pub/sub messaging service, such as Amazon SNS, promotes event-driven computing that statically decouples event publishers from subscribers, while dynamically allowing for the exchange of messages between them. An event-driven architecture also introduces the responsiveness needed to deal with complex problems, which are often unpredictable and asynchronous.

What is event-driven computing?

Given the context of microservices, event-driven computing is a model in which subscriber services automatically perform work in response to events triggered by publisher services. This paradigm can be applied to automate workflows while decoupling the services that collectively and independently work to fulfil these workflows. Amazon SNS is an event-driven computing hub, in the AWS Cloud, that has native integration with several AWS publisher and subscriber services.

Which AWS services publish events to SNS natively?

Several AWS services have been integrated as SNS publishers and, therefore, can natively trigger event-driven computing for a variety of use cases. In this post, I specifically cover AWS compute, storage, database, and networking services, as depicted below.

Compute services

  • Auto Scaling: Helps you ensure that you have the correct number of Amazon EC2 instances available to handle the load for your application. You can configure Auto Scaling lifecycle hooks to trigger events, as Auto Scaling resizes your EC2 cluster.As an example, you may want to warm up the local cache store on newly launched EC2 instances, and also download log files from other EC2 instances that are about to be terminated. To make this happen, set an SNS topic as your Auto Scaling group’s notification target, then subscribe two Lambda functions to this SNS topic. The first function is responsible for handling scale-out events (to warm up cache upon provisioning), whereas the second is in charge of handling scale-in events (to download logs upon termination).

  • AWS Elastic Beanstalk: An easy-to-use service for deploying and scaling web applications and web services developed in a number of programming languages. You can configure event notifications for your Elastic Beanstalk environment so that notable events can be automatically published to an SNS topic, then pushed to topic subscribers.As an example, you may use this event-driven architecture to coordinate your continuous integration pipeline (such as Jenkins CI). That way, whenever an environment is created, Elastic Beanstalk publishes this event to an SNS topic, which triggers a subscribing Lambda function, which then kicks off a CI job against your newly created Elastic Beanstalk environment.

  • Elastic Load Balancing: Automatically distributes incoming application traffic across Amazon EC2 instances, containers, or other resources identified by IP addresses.You can configure CloudWatch alarms on Elastic Load Balancing metrics, to automate the handling of events derived from Classic Load Balancers. As an example, you may leverage this event-driven design to automate latency profiling in an Amazon ECS cluster behind a Classic Load Balancer. In this example, whenever your ECS cluster breaches your load balancer latency threshold, an event is posted by CloudWatch to an SNS topic, which then triggers a subscribing Lambda function. This function runs a task on your ECS cluster to trigger a latency profiling tool, hosted on the cluster itself. This can enhance your latency troubleshooting exercise by making it timely.

Storage services

  • Amazon S3: Object storage built to store and retrieve any amount of data.You can enable S3 event notifications, and automatically get them posted to SNS topics, to automate a variety of workflows. For instance, imagine that you have an S3 bucket to store incoming resumes from candidates, and a fleet of EC2 instances to encode these resumes from their original format (such as Word or text) into a portable format (such as PDF).In this example, whenever new files are uploaded to your input bucket, S3 publishes these events to an SNS topic, which in turn pushes these messages into subscribing SQS queues. Then, encoding workers running on EC2 instances poll these messages from the SQS queues; retrieve the original files from the input S3 bucket; encode them into PDF; and finally store them in an output S3 bucket.

  • Amazon EFS: Provides simple and scalable file storage, for use with Amazon EC2 instances, in the AWS Cloud.You can configure CloudWatch alarms on EFS metrics, to automate the management of your EFS systems. For example, consider a highly parallelized genomics analysis application that runs against an EFS system. By default, this file system is instantiated on the “General Purpose” performance mode. Although this performance mode allows for lower latency, it might eventually impose a scaling bottleneck. Therefore, you may leverage an event-driven design to handle it automatically.Basically, as soon as the EFS metric “Percent I/O Limit” breaches 95%, CloudWatch could post this event to an SNS topic, which in turn would push this message into a subscribing Lambda function. This function automatically creates a new file system, this time on the “Max I/O” performance mode, then switches the genomics analysis application to this new file system. As a result, your application starts experiencing higher I/O throughput rates.

  • Amazon Glacier: A secure, durable, and low-cost cloud storage service for data archiving and long-term backup.You can set a notification configuration on an Amazon Glacier vault so that when a job completes, a message is published to an SNS topic. Retrieving an archive from Amazon Glacier is a two-step asynchronous operation, in which you first initiate a job, and then download the output after the job completes. Therefore, SNS helps you eliminate polling your Amazon Glacier vault to check whether your job has been completed, or not. As usual, you may subscribe SQS queues, Lambda functions, and HTTP endpoints to your SNS topic, to be notified when your Amazon Glacier job is done.

  • AWS Snowball: A petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data.You can leverage Snowball notifications to automate workflows related to importing data into and exporting data from AWS. More specifically, whenever your Snowball job status changes, Snowball can publish this event to an SNS topic, which in turn can broadcast the event to all its subscribers.As an example, imagine a Geographic Information System (GIS) that distributes high-resolution satellite images to users via Web browser. In this example, the GIS vendor could capture up to 80 TB of satellite images; create a Snowball job to import these files from an on-premises system to an S3 bucket; and provide an SNS topic ARN to be notified upon job status changes in Snowball. After Snowball changes the job status from “Importing” to “Completed”, Snowball publishes this event to the specified SNS topic, which delivers this message to a subscribing Lambda function, which finally creates a CloudFront web distribution for the target S3 bucket, to serve the images to end users.

Database services

  • Amazon RDS: Makes it easy to set up, operate, and scale a relational database in the cloud.RDS leverages SNS to broadcast notifications when RDS events occur. As usual, these notifications can be delivered via any protocol supported by SNS, including SQS queues, Lambda functions, and HTTP endpoints.As an example, imagine that you own a social network website that has experienced organic growth, and needs to scale its compute and database resources on demand. In this case, you could provide an SNS topic to listen to RDS DB instance events. When the “Low Storage” event is published to the topic, SNS pushes this event to a subscribing Lambda function, which in turn leverages the RDS API to increase the storage capacity allocated to your DB instance. The provisioning itself takes place within the specified DB maintenance window.

  • Amazon ElastiCache: A web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud.ElastiCache can publish messages using Amazon SNS when significant events happen on your cache cluster. This feature can be used to refresh the list of servers on client machines connected to individual cache node endpoints of a cache cluster. For instance, an ecommerce website fetches product details from a cache cluster, with the goal of offloading a relational database and speeding up page load times. Ideally, you want to make sure that each web server always has an updated list of cache servers to which to connect.To automate this node discovery process, you can get your ElastiCache cluster to publish events to an SNS topic. Thus, when ElastiCache event “AddCacheNodeComplete” is published, your topic then pushes this event to all subscribing HTTP endpoints that serve your ecommerce website, so that these HTTP servers can update their list of cache nodes.

  • Amazon Redshift: A fully managed data warehouse that makes it simple to analyze data using standard SQL and BI (Business Intelligence) tools.Amazon Redshift uses SNS to broadcast relevant events so that data warehouse workflows can be automated. As an example, imagine a news website that sends clickstream data to a Kinesis Firehose stream, which then loads the data into Amazon Redshift, so that popular news and reading preferences might be surfaced on a BI tool. At some point though, this Amazon Redshift cluster might need to be resized, and the cluster enters a ready-only mode. Hence, this Amazon Redshift event is published to an SNS topic, which delivers this event to a subscribing Lambda function, which finally deletes the corresponding Kinesis Firehose delivery stream, so that clickstream data uploads can be put on hold.At a later point, after Amazon Redshift publishes the event that the maintenance window has been closed, SNS notifies a subscribing Lambda function accordingly, so that this function can re-create the Kinesis Firehose delivery stream, and resume clickstream data uploads to Amazon Redshift.

  • AWS DMS: Helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.DMS also uses SNS to provide notifications when DMS events occur, which can automate database migration workflows. As an example, you might create data replication tasks to migrate an on-premises MS SQL database, composed of multiple tables, to MySQL. Thus, if replication tasks fail due to incompatible data encoding in the source tables, these events can be published to an SNS topic, which can push these messages into a subscribing SQS queue. Then, encoders running on EC2 can poll these messages from the SQS queue, encode the source tables into a compatible character set, and restart the corresponding replication tasks in DMS. This is an event-driven approach to a self-healing database migration process.

Networking services

  • Amazon Route 53: A highly available and scalable cloud-based DNS (Domain Name System). Route 53 health checks monitor the health and performance of your web applications, web servers, and other resources.You can set CloudWatch alarms and get automated Amazon SNS notifications when the status of your Route 53 health check changes. As an example, imagine an online payment gateway that reports the health of its platform to merchants worldwide, via a status page. This page is hosted on EC2 and fetches platform health data from DynamoDB. In this case, you could configure a CloudWatch alarm for your Route 53 health check, so that when the alarm threshold is breached, and the payment gateway is no longer considered healthy, then CloudWatch publishes this event to an SNS topic, which pushes this message to a subscribing Lambda function, which finally updates the DynamoDB table that populates the status page. This event-driven approach avoids any kind of manual update to the status page visited by merchants.

  • AWS Direct Connect (AWS DX): Makes it easy to establish a dedicated network connection from your premises to AWS, which can reduce your network costs, increase bandwidth throughput, and provide a more consistent network experience than Internet-based connections.You can monitor physical DX connections using CloudWatch alarms, and send SNS messages when alarms change their status. As an example, when a DX connection state shifts to 0 (zero), indicating that the connection is down, this event can be published to an SNS topic, which can fan out this message to impacted servers through HTTP endpoints, so that they might reroute their traffic through a different connection instead. This is an event-driven approach to connectivity resilience.

More event-driven computing on AWS

In addition to SNS, event-driven computing is also addressed by Amazon CloudWatch Events, which delivers a near real-time stream of system events that describe changes in AWS resources. With CloudWatch Events, you can route each event type to one or more targets, including:

Many AWS services publish events to CloudWatch. As an example, you can get CloudWatch Events to capture events on your ETL (Extract, Transform, Load) jobs running on AWS Glue and push failed ones to an SQS queue, so that you can retry them later.


Amazon SNS is a pub/sub messaging service that can be used as an event-driven computing hub to AWS customers worldwide. By capturing events natively triggered by AWS services, such as EC2, S3 and RDS, you can automate and optimize all kinds of workflows, namely scaling, testing, encoding, profiling, broadcasting, discovery, failover, and much more. Business use cases presented in this post ranged from recruiting websites, to scientific research, geographic systems, social networks, retail websites, and news portals.

Start now by visiting Amazon SNS in the AWS Management Console, or by trying the AWS 10-Minute Tutorial, Send Fan-out Event Notifications with Amazon SNS and Amazon SQS.


Cross-Account Integration with Amazon SNS

Post Syndicated from Christie Gifrin original https://aws.amazon.com/blogs/compute/cross-account-integration-with-amazon-sns/

Contributed by Zak Islam, Senior Manager, Software Development, AWS Messaging


Amazon Simple Notification Service (Amazon SNS) is a fully managed AWS service that makes it easy to decouple your application components and fan-out messages. SNS provides topics (similar to topics in message brokers such as RabbitMQ or ActiveMQ) that you can use to create 1:1, 1:N, or N:N producer/consumer design patterns. For more information about how to send messages from SNS to Amazon SQS, AWS Lambda, or HTTP(S) endpoints in the same account, see Sending Amazon SNS Messages to Amazon SQS Queues.

SNS can be used to send messages within a single account or to resources in different accounts to create administrative isolation. This enables administrators to grant only the minimum level of permissions required to process a workload (for example, limiting the scope of your application account to only send messages and to deny deletes). This approach is commonly known as the “principle of least privilege.” If you are interested, read more about AWS’s multi-account security strategy.

This is great from a security perspective, but why would you want to share messages between accounts? It may sound scary, but it’s a common practice to isolate application components (such as producer and consumer) to operate using different AWS accounts to lock down privileges in case credentials are exposed. In this post, I go slightly deeper and explore how to set up your SNS topic so that it can route messages to SQS queues that are owned by a separate AWS account.

Potential use cases

First, look at a common order processing design pattern:

This is a simple architecture. A web server submits an order directly to an SNS topic, which then fans out messages to two SQS queues. One SQS queue is used to track all incoming orders for audits (such as anti-entropy, comparing the data of all replicas and updating each replica to the newest version). The other is used to pass the request to the order processing systems.

Imagine now that a few years have passed, and your downstream processes no longer scale, so you are kicking around the idea of a re-architecture project. To thoroughly test your system, you need a way to replay your production messages in your development system. Sure, you can build a system to replicate and replay orders from your production environment in your development environment. Wouldn’t it be easier to subscribe your development queues to the production SNS topic so you can test your new system in real time? That’s exactly what you can do here.

Here’s another use case. As your business grows, you recognize the need for more metrics from your order processing pipeline. The analytics team at your company has built a metrics aggregation service and ingests data via a central SQS queue. Their architecture is as follows:

Again, it’s a fairly simple architecture. All data is ingested via SQS queues (master_ingest_queue, in this case). You subscribe the master_ingest_queue, running under the analytics team’s AWS account, to the topic that is in the order management team’s account.

Making it work

Now that you’ve seen a few scenarios, let’s dig into the details. There are a couple of ways to link an SQS queue to an SNS topic (subscribe a queue to a topic):

  1. The queue owner can create a subscription to the topic.
  2. The topic owner can subscribe a queue in another account to the topic.

Queue owner subscription

What happens when the queue owner subscribes to a topic? In this case, assume that the topic owner has given permission to the subscriber’s account to call the Subscribe API action using the topic ARN (Amazon Resource Name). For the examples below, also assume the following:

  •  Topic_Owner is the identifier for the account that owns the topic MainTopic
  • Queue_Owner is the identifier for the account that owns the queue subscribed to the main topic

To enable the subscriber to subscribe to a topic, the topic owner must add the sns:Subscribe and topic ARN to the topic policy via the AWS Management Console, as follows:


After this has been set up, the subscriber (using account Queue_Owner) can call Subscribe to link the queue to the topic. After the queue has been successfully subscribed, SNS starts to publish notifications. In this case, neither the topic owner nor the subscriber have had to process any kind of confirmation message.

Topic owner subscription

The second way to subscribe an SQS queue to an SNS topic is to have the Topic_Owner account initiate the subscription for the queue from account Queue_Owner. In this case, SNS first sends a confirmation message to the queue. To confirm the subscription, a user who can read messages from the queue must visit the URL specified in the SubscribeURL value in the message. Until the subscription is confirmed, no notifications published to the topic are sent to the queue. To confirm a subscription, you can use the SQS console or the ReceiveMessage API action.

What’s next?

In this post, I covered a few simple use cases but the principles can be extended to complex systems as well. As you architect new systems and refactor existing ones, think about where you can leverage queues (SQS) and topics (SNS) to build a loosely coupled system that can be quickly and easily extended to meet your business need.

For step by step instructions, see Sending Amazon SNS messages to an Amazon SQS queue in a different account. You can also visit the following resources to get started working with message queues and topics: